The invention relates to an automatic detection of pedestrians along with the measurement of distance from the moving vehicle. Now days, driver and pedestrian safety are becoming more and more important worldwide as the number of road accidents have increased significantly. These accidents are a major cause of loss of life and property. Recognition of pedestrian enables early warning which helps in reducing the probability of such accidents.
There are numerous approaches for detecting pedestrian and measuring their distance from the moving vehicle. Most of them involve use of sensors or cameras for detecting obstacles. These methods also involves use of typically, SIFT, SURF or other sophisticated image processing algorithms that are inherently robust in identifying identical stereo points resulting in accurate triangulation for position estimation. However, these image processing algorithms are due to inherent complex nature and demand exhaustive computation that in turn requires more processing power to retain good time performance of the system. One such method (US20070154068) provides estimating distance to an obstacle from a moving automotive vehicle equipped with a monocular camera. Specifically, the method includes image processing techniques used to reduce errors in real time of the estimated distance. A dimension e.g. a width is measured in the respective images of two or more image frames, thereby producing measurements of the dimension. This method provides a reduction in noise but it involves use of complex equations for measuring distance. Other such methods are less effective in night time (in poor light conditions) and in unfavorable weather conditions.
There is, therefore a need of a method and system to provide automatic detection of pedestrians and their distance from the moving vehicle with less error or noise in the tracked images and should involve less complexity. The method and system should also be capable of working in night mode and at the time of unfavorable weather conditions.